Improved BFO with Adaptive Chemotaxis Step for Global Optimization

This paper proposed an improved BFO with adaptive chemo taxis step for global optimization. A non-linearly decreasing exponential modulation model is proposed to optimize the chemo taxis step length. Four parameters: modulation index, coefficient, upper chemo taxis step length, and lower chemo taxis step length were discussed and considered to further improve the performance of BFO. To illustrate the efficiency of the proposed algorithms, two benchmark functions were selected as testing functions. Experiment results showed that appropriate parameters setting can greatly improve the speed of convergence as well as fine tune the search in the multidimensional space.